2015, Volume 17, Issue 3
Strategic Study of CAE >> 2015, Volume 17, Issue 3
The design and implementation of remote intelligent condition monitoring and diagnostic system for wind turbines
State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China
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Abstract
This paper researched the key technology of remote intelligent condition monitoring and diagnostic system for wind turbines, and described the development details of a system. The system, adopted the distributed architecture, consisted of four subsystems, which were the data acquisition subsystem, the real time data storage subsystem, the intelligent monitoring and diagnosis subsystem and the user interface subsystem. The intelligent monitoring and diagnosis subsystem used the knowledge base/inference engine structure. An advanced fuzzy expert system is developed for inference engine, and the vibration fault diagnosis rules for wind turbine is stored in the knowledge base. The effectiveness of the system is verified by diagnosing simulated wind turbine faults.
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References
[ 1 ] Association World Wide Energy. WWEA half year report 2014 [R]. 2014.
[ 2 ] 陈雪峰，李继猛，程 航，等. 风力发电机状态监测和故障诊 断技术的研究与进展[J]. 机械工程学报，2011，47(9)：45-52. link1
[ 3 ] 清华大学. 故障诊断专家系统辅助开发软件V1.0. 2013年12月 10日.
[ 4 ] Pan Juiyao，Guilherme N，Desouza Avinash. FuzzyShell：A large- scale expert system shell using fuzzy logic for uncertainty reasoning[J]. IEEE Transactions on Fuzzy Systems，1998，6(4)： 563-581. link1
[ 5 ] Wu Jianda，Liu Chuihong. An expert system for fault diagnosis in internal combustion engines using wavelet packet transform and neural network[J]. Expert Systems with Applications，2009， 36(3，Part 1)：4278-4286. link1
[ 6 ] Isermann Rolf. On fuzzy logic applications for automatic control，supervision，and fault diagnosis[C]// Systems，Man and Cybernetics，Part A：Systems and Humans，IEEE Transactions on， 1998，28(2)：221-235. link1
[ 7 ] Dou Dongyang，Zhao Yingkai. Fault diagnosis of rotating machinery using data mining and CLIPS- based expert system[C]// 2008 ISECS International Colloquium on Computing，Communication，Control，and Management，Proceedings，2008，2：127- 130. link1
[ 8 ] 李少华. 风力机故障特征提取与识别方法研究[D]. 北京：清华 大学，2011.
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